Module 3 Assessment: First Supervised Baselines
Assessment ID: ML-M03-QA01 Estimated active time: 35-45 minutes Status: Draft
Part A: Concept checks
Answer in one or two sentences.
- What is the majority-class baseline on this data, and why must it be reported?
- Which metric did you choose for the regression task, and why not accuracy?
- State your model's score and the gap over its matching baseline.
- What would a model scoring below the baseline tell you?
- Name one limitation of the data rather than of the model.
Part B: Applied task
Use the supplied synthetic Module 3 datasets.
- Train a median dummy regressor and a linear regression model for
quiz_score_day10. - Report test MAE for both.
- Train a most-frequent dummy classifier and a logistic regression classifier for
completed_module1_by_day10. - Report test accuracy for both.
- Inspect at least five predicted probabilities from the classifier.
Part C: Explanation
Explain both results against their baselines, and say which of the two tasks the data supports better.
Rubric
| Level | Evidence |
|---|---|
| Pass | Correctly separates regression and classification; excludes targets from features; uses train/test split; reports both dummy baselines and candidates; interprets MAE and accuracy in plain English; explains limitations. |
| Revise | Runs most of the modelling steps but misses one important explanation, baseline, or target/feature boundary. |
| Not yet | Uses the target as a feature, evaluates on training data only, omits baselines, or claims the model is ready for real learners. |
Safety rule
Do not use real personal, confidential, employer, client, health, financial, authentication, or sensitive data.